The first edition of TIME came out in 1923. Today, it remains an icon, and its cover page is coveted real estate.
TIME is one of the few legacy media brands that are still relevant in the digital age. The magazine covers make headlines around the internet, trigger tweet-storms, and produce some high quality memes.
TIME's creative director says that the cover 'crystallizes what is important.' And over a hundred years, many famous (and infamous) faces have graced TIME's cover page. Let us use this year-wise data to dig deep into TIME's cover.
Ever wonder who has been on who has been on the Time Magazine cover the most? Or, how many times has Donald Trump been on time magazine cover? We are going to use Gigasheet, a free online CSV viewer to explore Time Magazine data.
Read on to see how to explore the data, or just open the data yourself, no signup required.
This dataset contains all public figures people featured on the cover of TIME magazine since its inception in 1923. So, covers about events, non-famous folks, and others are not a part of this dataset. It was last updated in 2021, so we have 98 years worth of data.
In this blog, we will explore this data using Gigasheet and understand the following:
TIME describes itself as "[an] informative guide to what is happening in current affairs, politics, business, health, science and entertainment."
Use Gigasheet's Group By feature to see how many entries are in each category.
Grouping the dataset by the column 'Occupation', we see that:
1) 2,049 covers feature a public figure active in politics
2) 359 covers have featured business folks. Another 359 covers feature someone from the entertainment industry. So, its a tie!
3) And...its only 182 for science
Let us dig deeper and find out which are the top five categories. All you need to do is sort the groups in descending order. Right click on the column you are using for the Row Count aggregate function. (Here, we are using the column 'Name'.) Then, select Sort Sheet - 9 to 1
The top 5 results are Politics, Entertainment, Business, Military, and Sports. Science and health couldn't make it here!
You can also visualize this data by selecting the groups and the row count, and using the Chart Range feature.
Learn more about Grouping Data here
What about the most popular people? Grouping by the column 'Name', we see that the name on top is Richard Nixon.
Or have they? Let us compare decade-wise TIME cover trends, starting with the roaring 1920s.
We only have year-wise data for this dataset. So, let us filter out the 1920s data. (Here, we are also saving this filter with the name 'The 20s' for future use.)
Next, we will group by Occupation again, like we did for the last section.
Here is what the Occupation distribution was like in the 20s. There are fewer categories, but Politics, Business, and Military are still the top three!
And here is the same data for the 2020s....
Politics seems to be a favorite category, as most influential public figures in history have been government leaders and politicians. So, let us filter this dataset to extract the 2,049 rows where the Occupation is 'Politics & Gov.'
Grouping this dataset by year, and visualizing it as columns, we get a rather dense graph. You can see the values when you hover over individual bars like this:
But what if we wanted to visualize this data by decade?
Say, we want to check which were the most popular categories in the first five decades of the magazine's publication. What do we do?
First, let us filter out the rows for these decades (1920s, 1930s, 1940s, 1950s, and the 1960s.) The simplest way is to filter all the rows where the year is less than 1970.
Then, we will play around with the field 'Year.'
Gigasheet will split each value in the column by 19 and render two columns.
Now, we have the last two digits of each year, but we're not done yet! Remember we need to group by decade. So, let us separate these two digits.
First, we will change the data type of the split column to 'Number.'
Gigasheet will add a new column with the suffix " - as number (integer)" to indicate this change.
Next, go to Function -> Calculations. Select the new column with integer values, and divide it by 10.
And, we will get a new column:
And next, you know the drill! Let us split this column by the decimal value, take the first half and multiply it by 10. After a couple of steps, we have a new column that indicates what decade it is. Let us rename it 'Decade.'
We have extracted the decade from the year's value using Gigasheet's calculations, without writing any code.
Let us use this column to group data. And since we want to find out the most popular category in each decade, let us further group by 'Occupation.'
By taking a look at this data, we can conclude that:
Let us play around further, and apply filters on these groups. TIME was always heavily focused on media and politics, but what about, say, fashion moguls?
Filtering the entire dataset for those with the Occupation 'Fashion':
No one from the fashion industry was featured in the 20s. The 30s had one. And the next three years had 2.
Well, what about music? Let's check.
This is how it looks like as a bar graph. Clearly, the 40s were a good time for music.
"TIME - Person of the Year" is an annual issue of that features a person, a group, an idea, or an object that, according to TIME, has made the greatest impact in that year.
First up, let us filter out all the individuals who have been awarded 'Person of The Year' by adding the condition that the value of the column 'POY' should be 'Y.'
The resulting dataset has 130 rows. So, in the past 98 years, the number of people who have appeared on the cover and won POY is 130.
Have any of these individuals ever won POY more than once? Let's check. Grouping by 'Name', we get the following results. Franklin D Roosevelt was crowned Person Of The Year thrice, in the years 1933, 1935, and 1942.
Did he appear on the cover more than thrice, even if he didn't win POY? Well, we will simply remove the filter. That gives us the result that Franklin D. Roosevelt has been featured on the cover a total of 13 times.
Big data analysis can be fun, insightful, and comes in handy while making decisions. But, not all spreadsheet tools can handle big data. This is why you need Gigasheet.
Gigasheet is a FREE data analysis tool that opens large data files with ease, no matter where they are stored. It supports a variety of file formats, offers quick data grouping and filtering, and is completely no-code. So, if you have a large log file waiting to be analyzed, and Excel doesn't cut it, you know what to do!
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